Preliminary observations of nivation processes, Cathedral Massif, Northwestern British Columbia, Canada
Bibliographic record
Abstract
Nivation, the suite of weathering and transportation processes attributed to late-lying snowpatches, is linked to the formation of cryoplanation terraces (CTs). CTs resemble giant staircases arranged in repeating sequences of low-gradient treads and steep scarps that extend over hundreds of meters. The nivation hypothesis of CT development has been supported in recent literature examining weathering and erosion trends, but the mechanisms involved in transporting sediment across CT treads remain underinvestigated. Sorted stripes, a type of patterned ground encountered on CT treads, have been linked to efficient snow meltwater flow across low gradients, indicating that these features could be an important component of CT formation. In this study, we use short-term soil thermal and moisture records, particle-size analysis, and apparent thermal diffusivity calculations to examine periglacial processes operating on two incipient CTs. Initial results indicate that: (1) the coarse (boulder and cobble size) portions of sorted stripes function as subsurface channels for sediment transportation across gently sloping CT treads (generally < 12°) by flowing water; (2) hillslope hydrology is an important component of the erosion processes sculpting upland periglacial environments; and (3) late-lying snowbank environments are highly dynamic during warm weather, with large amounts of sediment transported over short periods.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".